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machine learning, deep learning, data visualization, and applied analytics for multi-modal datasets. Technical proficiency with Python, R, SQL, SPSS, Tableau. Architectural and design software expertise
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application of advanced deep learning models, with an emphasis on techniques such as knowledge distillation. The candidate will engage in research involving time-series analysis, including modeling, forecasting
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upon future funding. Qualifications Required Education and Experience Appropriate PhD in a related field. Preferred Qualifications Experience with machine learning and deep neural network techniques
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organization skills. Experienced in workflow design and technical documentation. PREFERRED QUALIFICATIONS Experience developing AI methods for environmental data sets including working with deep learning
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Measure Theory : Leveraging foundational mathematical frameworks to design robust modeling approaches. 2) Deep Learning : Exploring cutting-edge techniques such as multimodal data integration, diffusion